Agent-Based Trading System

A multi-agent AI trading system where specialized agents communicate and collaborate to make team-based trading decisions — like having an AI trading desk.

Agent Architecture:

• Market Analyst Agent: Scans charts, news, and on-chain data
• Risk Manager Agent: Approves/rejects trades, sizes positions
• Executor Agent: Routes orders for best fill
• Portfolio Manager Agent: Allocates capital across strategies
• Researcher Agent: Backtests and discovers new strategies

Agent Communication:

• Structured message passing between agents
• Consensus mechanism for trade decisions
• Conflict resolution (risk vetoes analyst)
• Audit log of all agent conversations
• Human-in-the-loop override capability

AI Models:

• GPT-4 / Claude for reasoning and analysis
• FinBERT for sentiment classification
• LSTM for price prediction
• Reinforcement learning for execution
• Custom fine-tuned models support

Customization:

• Agent personality configuration
• Risk tolerance tuning per agent
• Strategy preference settings
• Communication frequency control
• Enable/disable specific agents

Tech Stack:

• Python + LangChain / AutoGen framework
• OpenAI / Anthropic API integration
• PostgreSQL for agent memory
• WebSocket real-time agent chat UI
• Docker deployment